The burden of proof that lockdowns work is clearly on those imposing and supporting lockdowns. Lockdown skeptics are under no obligation whatsoever to show lockdowns do not work.
Lockdowns are a burden, an imposition, a severe restriction of liberty. It is certain and indisputable that they cause harm. Therefore, if lockdown supporters cannot prove with something approaching certainty they work, then lockdowns cannot and should not be imposed.
Lockdown supporters know, as we all know, that lockdowns will and have thrown people out of work, will and have swollen welfare rolls, caused recessions or worse, led to suicides, delayed needed medical treatments, even caused death (NPR story of one case; when I showed this to one lockdown lover he wondered if this poor woman might have died from an obscure form of COVID-19 instead). Police have been ticketing and citing people for the “crimes” of playing soccer and sitting in parks. In Michigan, the Governor decreed that people could not travel between their homes.
Governments instituted lockdowns in an arbitrary and capricious manner, and they have given no indication what objective verifiable criteria will be used to lift them. In truth, the criteria will be the same as those used to institute them: when politicians think they will no longer be blamed for the virus causing deaths. Fear drives the crisis in our leaders just as much as it does in citizens.
This is why when I showed this graph below, I said we could not conclude from it that lockdowns work. It may be, as some critics are saying, that I cannot prove lockdowns don’t work from this graph. I do not have to. I have no such obligation.
Other say that this graph doesn’t account for population density (as if no-lockdown Tokyo, Taipei and Rio aren’t dense), or obesity, age, sex, smoking status, weather, lockdown timing and severity, and anything else. Well, I said as much. (The graph does in a weak way say something about population density, but forget it.)
I said that the only way to tell that lockdowns worked was to gather all possible data on cause, including lockdown status (it’s timing, severity, compliance at the individual level from those that died, and from a good sample of those that didn’t, see just what, exactly, killed, and what did not kill. This is not impossible. But it hasn’t happened, and almost certainly won’t, not worldwide. Oh, we’ll see lots of BS stats studies, with wee p-values aplenty. But none of it, I predict, will reach the level of proof.
The only claim I make is that is certain is you cannot conclude from this data that lockdowns worked.
Now, before I had a chance to go through it, WJ Keller sent me data from Oxford, which claims to have quantified the unquantifiable in a much better fashion that I. It only look at 166 countries, whereas we did over 200. But they do much more with theirs, looking at timing for various restrictions in liberties (school and business closings, house arrest, and a few other loosey goosey things, but no population size!). These, like my Y/N measure, are all at the country level.
I can tell you right now this new data won’t prove lockdowns work. We have already seen, just in decrepit Europe alone, that Belgium, UK, Andorra, Spain, Italy, and France, all locked down, had higher mortality rates than Sweden, with Belgium being more than twice as high. Taiwan did not lock down, but did bar travel in and out to some extent, and had only 7 deaths. None of the measures Oxford used can “correct” these differences.
Another criticism (from a PhD professor at big place) said the data can’t be trusted, not everywhere. Too true! I pointed out to him that you can’t move from “I have bad data” to “I know lockdowns work based on data”. He disappeared. Another soy-faced PhD economist said the analysis “disgusted” him, then he blocked me on Twitter, presumably to prevent further dyspepsia.
Another bad argument is that a majority agreed, and still agree, to willingly to have their movements restricted. This is absurd, because they could have locked their own selves down and let the minority who wanted to remain at liberty be free. But, no. The majority agreed to remove everyone’s liberty, in the belief that they themselves would be protected. Fear rules.
That they majority agree does not make the elimination of liberty good or legal. Might in arms or through show of hands does not make right, though many living in democracies are accustomed to thinking it does, since so much is put to a vote. To say that a majority makes something good or evil is an obvious fallacy.
The usual argument in favor of lockdowns runs like this: We know lockdowns work because lockdowns work, which is why we locked down, because if we didn’t lock down it would have been worse. It’s science.
Lockdowns have known costs, but unproved benefits. Some say that we had to lock down to “flatten the curve”, and because we locked down therefore the curve was flattened. This is a circular argument. It is just another way of saying “lockdowns work because lockdowns work.” It still has to be proved lockdowns flatten curves, and that flattening curves is good.
A response to that, given by some, is to say “It’s obvious lockdowns flatten curves”, to which we reply “It’s obvious they do not.” This is a futile discussion.
A better response is to say “Lockdowns force people inside and lessen their contact with others, therefore limiting the spread of the virus.” This is countered by “Lockdowns force healthy and sick into tight quarters, therefore enhancing the spread of the virus.” This is true, too, at least in the US, because the form of the lockdowns were to throw people, younger and healthier on average, in small businesses out of work, and force them to stay home, sometimes with older relatives, who are of course older and unhealthier on average. It also allowed people out for limited times, to shop for groceries and the like, and then forced them back inside.
Stores owned by oligarchs were allowed to remain open. This implies the virus, as many joked, could tell the difference between Costco, which wasn’t locked down, and (say) a small jewelers, which was forced to close. The virus didn’t dare infect Costco shoppers, but those searching for wedding rings would have dropped dead on the spot.
The answer to the jewelry stores is to say any limitation of human contact, short of causing people to starve, helped in limiting spread of the virus. This is another way of saying lockdowns work because lockdowns work. It is far from clear allowing “essential” businesses to remain open and the forced closing (or other disruptions) of “inessential” businesses made any difference whatsoever to the spread of the virus.
Some said things like this: “increased spread of virus causes countries to respond with lockdowns, not lockdowns cause increased spread”. This is another way of saying lockdowns work because lockdowns work. The virus did not cause any government to lockdown: politicians caused lockdowns based on the beliefs that lockdowns spared live—and saved political reputations.
Now it may be the case that, overall, lockdowns did somewhere slow and even in places stopped the spread of the virus. This is nowhere proved, but it is a possibility. We do not claim this never happened, but if it did, the lockdown still has to be judged by its successes and its harms.
Andrew Cuomo in full-pander mode infamously and said in March that if his dictatorial orders “saved just one life, then it will be worth it.” This is false, since the lockdowns caused at least some deaths, with some evidence pointing to many deaths. Death in any case is only one “metric”. It cannot be the only one, or else we would ban driving. The whole of the cost of the lockdown must be compared with the demonstrated, and not just asserted, benefit.
There are some who point to graphs showing infection counts with indicators when lockdowns begin, then claiming the infection counts immediately decrease. Cases are caused by the virus spreading, and the virus would have already spread before the lockdown was imposed. There is no chance actual cases would have immediately dropped after a lockdown, only some time after.
The confusion comes because cases are only noted when measured. A lockdown can certainly cause measurements to decrease, as people decide not to go and get tested. Because of this, the only way to measure the effect of a lockdown is to count illness and deaths, and then prove these would have been greater without the lockdown.
It’s not that it is impossible to do this. It’s that nobody has done it. Many have asserted it, but, not to bore you, but this is just saying lockdowns work because lockdowns work.
It’s not just me! Calling it like it is: “Many lockdown regulations were seemingly thumb sucks.” From South Africa.
I got to these too late to add to the main lockdown post.
In the US, eight states never locked down. They were, with deaths per million (as of 17 May, using the COVID Tracking Project’s numbers): Iowa (111), Oklahoma (73), Nebraska (64), North Dakota (56), South Dakota (50), Arkansas (32), Utah (25), and Wyoming (14). Be careful with these numbers, as they are stated in relative terms. Wyoming, for example, has about 580 thousand souls, and had only 8 coronavirus deaths.
The states with the harshest lockdowns were California (83), Illinois (330), Michigan (490), New York (1162), New Jersey (1166).
It’s obvious that there are many more differences between states than lockdown status (here’s a full list, using different data sources; same story, though). But it’s also plain that there is no way, none at all, to claim using these comparisons that lockdowns were successful.
Since almost all of California’s deaths were in the LA area (though the entire massive state was officially locked down), most deaths in Illinois were in the Chicago area, Michigan’s around Detroit, and New York and New Jersey’s around the New York City metropolitan area, it’s very likely population density played a role. Which argues against lockdowns, since everybody had to be cooped up in tight quarters.
So sure were experts and journalists sure that lockdowns were necessary, and could not be relaxed until who knows what happened, that predictions of doom and gloom for states reinstituting liberty are a staple of the news. The New York Times trotted out “models” which “Project Sharp Rise in Deaths as States Reopen”. That the previous models they relied upon to preach the apocalypse failed did not deter them from using them again.
The fabulously flawed Fauci wrung his hands together and warned “consequences could be really serious” if states opened before he gave them permission. Other journalists had to be satisfied with noting cases increased in Texas after they “relaxed” their anti-liberty measures. Well, cases can go to 0 if no tests are made, or they can rocket if testing increases. This is why what counts are deaths and hospitalizations and the like. These did not increase in Texas.
The most hysterical predictions were saved for Georgia, because they were one of the first states to restore stolen liberties. Experts and pundits were sure this was the end. This is why some of them took to reporting, not new deaths, but total deaths. Total deaths can only increase, even as rates drop to zero. But publicizing that increase is a good way to boost fear. A model touted by CNN at the end of April said deaths could double! Sadly for the doomsayers, Georgia’s death rate continued to fall.
There was almost no reporting on states which did not remove liberty from its citizens. Except early on, when each new death was blazoned across every screen journalists could get their greasy fingers on. This is probably partly due to dishonesty. Most journalists gave up on honesty a long time ago, justifying the means of lying in their saving-the-world ends. But it’s also muleheadedness. The experts were so sure they were right, they refused to look at data proving them wrong.
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Update This is twitter thread in answer to the bad comments and emails I received. Cut and paste what you like, because all my tweets die in 7 days from coronavirus (not a joke).